Machine learning can help prevent hospitalizations
Hospitalizations often are the result of worsening conditions that weren't properly managed while the patient was at home. It doesn't take artificial intelligence to tell you that a preventable hospitalization is not good. A hospital is not a bed-and-breakfast. No one says,"hey, for fun, let's get a hospital room overlooking the parking garage this weekend." A preventable hospitalization is by definition one that could have been prevented.
One example of an AI approach is machine learning. Machine learning is not about you learning how to use machines. It is when a set of computer algorithms try to perform a particular task or generate a specific insight without following explicit instructions. The algorithms will instead look for patterns in data and try to determine what to do based on these patterns.
If you think that other insurance companies can do this, Vivek Garipalli, CEO and Co-Founder of Clover Health, has a response: working with machine learning"is not in the DNA of traditional payors. They are financial companies and not tech companies.
arents are physicians. I grew up with health care as a topic," and how he spent years on the operational side of health care.sleep disorder diagnosis center and brought in local doctors," he added."This made me realize hphysicians and the challenges that they faced." Subsequently, he"urned it around to profitability.
Ian Blumenfeld, Chief Data Scientist, and Brian Johnson, Senior Engineer at Clover Health, recently wrote
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